MétaCan
Menu
Back to cohort
Record W7098002590

Keeping Warm on the NYO&W in the Diesel Era Modeling the Unique-to-the-O&W Heater Car in HO Scale

2015· article· en· W7098002590 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsTrainBridge (graph theory)Scale (ratio)Power (physics)Truck
DOInot available

Abstract

fetched live from OpenAlex

One of the most distinctive cars on the O&W were the two heater cars – cars homemade by the Middletown shops to provide steam heating for passenger trains once the road dieselized. Fellow society member Karl Diefenderer is offering a HO scale version of these cars in cast resin. He writes: “I am really excited to be able to make these kits. Having waited too long for someone else to produce the O&W Heater Tenders, I decided to give it a try. ” As he points out, these cars are unlikely to get produced by any manufacturer, due to their limited mass appeal. I model the New York, Ontario & Western as if it were still going strong into the late 1990’s as part of an alternative-to-Conrail bridge route made up of the NYS&W, the NYO&W, and the D&H. So most of the time, I don’t get to make those great O&W kits that society members make available – they are out of my time period. However, I got pretty excited when Karl posted to our newsgroup that he worked out a cast resin version of a heater car in HO Scale. After all, even in the 1990s, the NYO&W, like many other freight-only railroads, would not spend precious funding on converting their office train to head end power (HEP). Finally, an O&W prototype that I could model!

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.091
GPT teacher head0.260
Teacher spread0.169 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same topicTransport and Economic PoliciesFrench-language works237,207